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Journal : Journal of Computer Networks, Architecture and High Performance Computing

Comparison of Evaluation Image Segmentation Metrics on Sasirangan Fabric Pattern Finki Dona Marleny; Mambang Mambang
Journal of Computer Networks, Architecture and High Performance Computing Vol. 4 No. 2 (2022): Article Research Volume 4 Number 2, July 2022
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v4i2.1479

Abstract

Sasirangan fabric is a typical fabric from the South Kalimantan area. Sasirangan fabric patterns or motifs have a unique archetype that is different from other typical fabrics in Indonesia. The design of Sasirangan fabric is formed from the process of juju or seam. The pattern of Sasirangan fabric that has this uniqueness can be segmented into a more meaningful shape so that it is easy to analyze. The image segmentation that will be tested is the basic pattern of Sasirangan fabric with a random sample to compare the results of the evaluation of the metric evaluation of the image segmentation process from the Sasirangan fabric pattern. Image segmentation is a different segmentation with certain characteristics, namely using the compact watershed approach, canny filter, and morphological geodesic active contours method in the evaluation of image segmentation metrics using precision-recall, which serves to evaluate the quality of the classifier's output. After the image segmentation process is evaluated, the Sasirangan fabric pattern is grouped using the K-means algorithm as a different labelling strategy. This labelling process uses the K-means algorithm to better match details but can be unstable because it relies on random initialization. Alternatives to balance the unstable labelling process using the means algorithm can use discretization. The addition of the K-means method with discretization can create fields with geometric shapes that are pretty flat. The segmentation with Sasirangan fabric with a full motif or data number four 741.78s, results in processing the fastest and the longest computational time on data number two 120.79s.
Comparison of Evaluation Image Segmentation Metrics on Sasirangan Fabric Pattern Marleny, Finki Dona; Mambang, Mambang
Journal of Computer Networks, Architecture and High Performance Computing Vol. 4 No. 2 (2022): Article Research Volume 4 Number 2, July 2022
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v4i2.1479

Abstract

Sasirangan fabric is a typical fabric from the South Kalimantan area. Sasirangan fabric patterns or motifs have a unique archetype that is different from other typical fabrics in Indonesia. The design of Sasirangan fabric is formed from the process of juju or seam. The pattern of Sasirangan fabric that has this uniqueness can be segmented into a more meaningful shape so that it is easy to analyze. The image segmentation that will be tested is the basic pattern of Sasirangan fabric with a random sample to compare the results of the evaluation of the metric evaluation of the image segmentation process from the Sasirangan fabric pattern. Image segmentation is a different segmentation with certain characteristics, namely using the compact watershed approach, canny filter, and morphological geodesic active contours method in the evaluation of image segmentation metrics using precision-recall, which serves to evaluate the quality of the classifier's output. After the image segmentation process is evaluated, the Sasirangan fabric pattern is grouped using the K-means algorithm as a different labelling strategy. This labelling process uses the K-means algorithm to better match details but can be unstable because it relies on random initialization. Alternatives to balance the unstable labelling process using the means algorithm can use discretization. The addition of the K-means method with discretization can create fields with geometric shapes that are pretty flat. The segmentation with Sasirangan fabric with a full motif or data number four 741.78s, results in processing the fastest and the longest computational time on data number two 120.79s.
Co-Authors Ade Putri Maharani Adha, Muhammad Iqbal Ahadi Ningrum, Ayu Ahmad Faisal Hamidi Ahmad Hidayat Ahmad Hidayat Ahmad Nawawi Ahmad Riki Renaldy Akhmad Baddrudin Antonia Yenitia Aqli, Ahmad Aulia Fitri Aulia Fitri Aulia Fitri, Aulia Ayu Ahadi Ningrum Bambang Lareno, Bambang Bayu Nugraha Bima Wicaksono Damayanti, Alfisah Dixky Dixky Elisa Fitriana Fatahulrahman, Maman Fitriansyah, Muhammad Gazali, Mukhaimy Hamdani Hamdani Haniffah Sri Rinjani Hudatul Aulia Ihdalhubbi Maulida Ihsanudin Indah Wulandari Jaya Hari Santoso Johan Wahyudi Johan Wahyudi, Johan Kamaruddin Kamarudin Kamarudin Kamarudin Kartika Kartika Liliana Swastina Lufila, Lufila M Samsul Hasbi M Samsul Hasmi Maman Fatahulrahman Mambang Mambang Fitriansyah Maria Ulfah Maulida, Ihdalhubbi Meila Izzana, Meila Melda Melda Miranda Miranda Muhammad Khairul Akbar Muhammad Noval Muhammad Riduan Syafi’i Muhammad Satrio Ayuba Muhammad Tantowi Jauhari Muhammad Zaini Bakri Muhammad Ziki Elfirman Muhammad Ziki Elfirman Muhammad Ziki Elfirman, Muhammad Ziki Muhammad Zulfadhilah Mukhaimy Gazali Mutmainah Mutmainah Nahdi Saubari Nalo Valentino Ningrum, Ayu Ahadi Nor Azizah Novita Sari Novriansyah, Irvan Nur Hafiz Ansari Nur Meilianti Maulida Nurhaeni Nurhaeni Prastya, Septyan Eka Putri Putri Putri Putri, Putri Rahmini Rahmini Reni Emiliya Ricardus A P, Ricardus A Risma Maulida Risma Risma Rismawati Rismawati Rizkian Muhammad Fikri Ropikah Ropikah Rudy Ansari Rudy Ansari Rudy Ansari, Rudy Samita, Mambang Sandro Nesta Pembriano Sa’adah Sa’adah Septian Eka Prastya Septyan Eka Prastya Septyan Eka Prastya Subhan Panji Cipta Susanti, NurAina Tasya Salsabila Theresia Kurniati Seran Tiara, Astia Rahma Tumanggor, Agustina Hotma Uli Winda Astria Nuansa Saputri Winda Astria Nuansa Saputri Windarsyah Windarsyah Wulandari Febriani Yulisa Suryana Yuslena Sari, Yuslena